Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy

Patient-derived tumor explant models of tumor immune microenvironment reveal distinct and reproducible immunotherapy responses

Tumor-resident immune cells play a crucial role in eliciting anti-tumor immunity and immunomodulatory drug responses, yet these functions have been difficult to study without tractable models of the tumor immune microenvironment (TIME). Patient-derived ex vivo models contain authentic resident immune cells and therefore, could provide new mechanistic insights into how the TIME responds to tumor or immune cell-directed therapies. Here, we assessed the reproducibility and robustness of immunomodulatory drug responses across two different ex vivo models of breast cancer TIME and one of renal cell carcinoma. These independently developed TIME models were treated with a panel of clinically relevant immunomodulators, revealing remarkably similar changes in gene expression and cytokine profiles among the three models in response to T cell activation and STING-agonism, while still preserving individual patient-specific response patterns. Moreover, we found two common core signatures of adaptive or innate immune responses present across all three models and both types of cancer, potentially serving as benchmarks for drug-induced immune activation in ex vivo models of the TIME. The robust reproducibility of immunomodulatory drug responses observed across diverse ex vivo models of the TIME underscores the significance of human patient-derived models in elucidating the complexities of anti-tumor immunity and therapeutic interventions.

Metabolites and metabolic pathway reactions links to sensitization of immunotherapy in pan-cancer

Metabolic features are crucial in tumor immune interactions, but their relationship with antitumor immune responses is not yet fully understood. This study used Mendelian randomization analysis to identify the causal relationships between blood metabolites and immune cells and to evaluate the effects of metabolic pathways and reactions on antitumor immune responses in various cancers. Levels of 156 metabolites exhibited significant associations with selected immune cells. Metabolic enrichment analysis indicated laurate, propionyl-carnitine, carnitine and l-acetylcarnitine are enriched in fatty acid (FA) metabolism pathways. These enriched pathways are significantly correlated to CD8+ T cell function signatures in tumor environment and favor better prognostic outcomes. Metabolic reactions contributing to better immunotherapy responses were identified and used to establish the immuno-metabolic reaction score (IMRS). IMRS were significantly correlated to CD8+ T cell infiltration levels and CD8+ T cell signature scores in either 10× Visium spatial transcriptomic or RNA-seq samples. Finally, IMRS could significantly predict favorable survival outcomes in different cancer patients treated with immunotherapy. Our study revealed a link between certain metabolites and their related metabolic pathways to tumor immune landscape and immune functions. These results could promote the accurate stratification of patients before treatment and improve the efficacy of immunotherapy.

Pan-cancer characterization of m6A-mediated regulation of T cell exhaustion dynamics and clinical relevancies in human cancers

T cell exhaustion (TEX) is a major barrier to effective immunotherapy. The role of N6-methyladenosine (m6A) modification in regulating immune cell function has been recognized, but its impact on TEX dynamics across cancer types and clinical outcomes remains unclear. Here, we conducted a pan-cancer analysis integrating multi-omics data from cell lines, single-cell RNA sequencing, and pan-cancer and immunotherapy datasets to explore the dynamic interplay between m6A modification and TEX. We found that m6A modification influences key TEX-associated genes at both the cellular and single-cell levels, with distinct expression patterns across the exhaustion spectrum. Based on m6A-TEX interactions, three pan-cancer subtypes were identified, each with unique molecular profiles, immune phenotypes, and survival outcomes. The TexLm6AL subtype, characterized by low m6A activity and low TEX, correlated with high immune infiltration, increased cytolytic activity, and favorable survival, whereas the TexLm6AH and TexHm6AH subtypes with higher m6A activity were associated with poorer survival. Multivariate analysis confirmed the prognostic value of this classification independent of traditional clinical factors. Moreover, m6A-TEX crosstalk influenced responses to immune checkpoint blockade therapies. Our findings provide novel insights into the role of m6A in TEX regulation and underscore the potential of m6A regulators as biomarkers and therapeutic targets for advancing cancer immunotherapy.

Identification of lactylation-associated fibroblast subclusters predicting prognosis and cancer immunotherapy response in colon cancer

BACKGROUND

Lactylation plays an important role in tumor progression. This study aimed to clarify the impact of lactylation on cancer-associated fibroblasts(CAFs).

METHODS

Single-cell and bulk RNA sequence data, along with survival information, were obtained from TCGA and GEO datasets. Significant lactylation-associated genes were acquired by differential analysis and used to construct a prognostic model via Cox and LASSO regression analyses. Next, single-cell analysis, enrichment and pathway analysis, pseudotemporal trajectory and survival analysis were used to identify significant lactylation-associated fibroblast subclusters in colon cancer. IMvigor210 and PRJEB23709 cohorts were applied to assess the response to immunotherapy. In vitro experiments were conducted to explore how lactylation affect fibroblasts.

RESULTS

We established a lactylation-associated prognostic model with 17 risk genes in TCGA and further validated it in GEO datasets. Single-cell analysis revealed the lactylation level of fibroblasts in colon cancer was greater than that in normal tissues. Moreover, five lactylation-associated fibroblast subclusters were identified via the NMF algorithm. Patients with lower scores of FB_2_CALD1, FB_3_TPM4 and FB_4_AHNAK subclusters had better clinical prognosis in colon cancer and were more likely to benefit from immunotherapy. Further experiments demonstrated that lactylation could enhance the proliferation, migration and invasion ability of fibroblasts and up-regulate the expression of COL1A1, which was similar to the effect of colon cancer cells.

CONCLUSION

This study identified key fibroblast subclusters with prognostic value and implied that lactylation might help transform fibroblasts into CAFs in colon cancer for the first time, which provides new paths for understanding the evolution of CAFs and cancer therapeutic strategies.

TCGEx: a powerful visual interface for exploring and analyzing cancer gene expression data

Analyzing gene expression data from the Cancer Genome Atlas (TCGA) and similar repositories often requires advanced coding skills, creating a barrier for many researchers. To address this challenge, we developed The Cancer Genome Explorer (TCGEx), a user-friendly, web-based platform for conducting sophisticated analyses such as survival modeling, gene set enrichment analysis, unsupervised clustering, and linear regression-based machine learning. TCGEx provides access to preprocessed TCGA data and immune checkpoint inhibition studies while allowing integration of user-uploaded data sets. Using TCGEx, we explore molecular subsets of human melanoma and identify microRNAs associated with intratumoral immunity. These findings are validated with independent clinical trial data on immune checkpoint inhibitors for melanoma and other cancers. In addition, we identify cytokine genes that can be used to predict treatment responses to various immune checkpoint inhibitors prior to treatment. Built on the R/Shiny framework, TCGEx offers customizable features to adapt analyses for diverse research contexts and generate publication-ready visualizations. TCGEx is freely available at https://tcgex.iyte.edu.tr , providing an accessible tool to extract insights from cancer transcriptomics data.

Biological and clinical significance of tumour-infiltrating lymphocytes in the era of immunotherapy: a multidimensional approach

Immune-checkpoint inhibitors (ICIs) have improved clinical outcomes across several solid tumour types. Prominent efforts have focused on understanding the anticancer mechanisms of these agents, identifying biomarkers of response and uncovering resistance mechanisms to develop new immunotherapeutic approaches. This research has underscored the crucial roles of the tumour microenvironment and, particularly, tumour-infiltrating lymphocytes (TILs) in immune-mediated tumour elimination. Numerous studies have evaluated the prognostic and predictive value of TILs and the mechanisms that govern T cell dysfunction, fuelled by technical developments in single-cell transcriptomics, proteomics, high-dimensional spatial platforms and advanced computational models. However, questions remain regarding the definition of TILs, optimal strategies to study them, specific roles of different TIL subpopulations and their clinical implications in different treatment contexts. Additionally, most studies have focused on the abundance of major TIL subpopulations but have not developed standardized quantification strategies or analysed other crucial aspects such as their functional profile, spatial distribution and/or arrangement, tumour antigen-reactivity, clonal diversity and heterogeneity. In this Review, we discuss a conceptual framework for the systematic study of TILs and summarize the evidence regarding their biological properties and biomarker potential for ICI therapy. We also highlight opportunities, challenges and strategies to support future developments in this field.

HVEM as a tumor-intrinsic regulator in non-small cell lung cancer: Suppression of metastasis via glycolysis inhibition and modulation of macrophage polarization

Herpes virus entry mediator (HVEM) is a novel costimulatory molecule which mediates stimulatory or inhibitory signals in immune responses which makes it an attractive target in cancer therapeutics. However, the role of tumor cell intrinsic HVEM on tumor biology remains largely unknown. In this study, We demonstrated that CK+HVEM+ tumor correlates with better survival using Multiplex immuno histochemistry (mIHC) in Human Lung Adenocarcinoma Tissue microarray. Next, we showed that HVEM knockdown promoted NSCLC cell invasion and metastasis in vitro whereas exhibited no effect on proliferation. Conversely, HVEM overexpression results in the opposite phenotype. Meanwhile, the conclusion were further confirmed in vivo experiment that overexpression of HVEM reduced the invasion and metastasis of NSCLC whereas no effect on tumor mass. Besides, vivo experiment showed that M1 TAMs in the HVEM overxrpression group was increased and the proportion of M2 macrophages was decreased compared to the vector group. Mechanistically, The C-terminal 228-283 amino acid segment of HVEM protein interacts with the N-terminal 1-383 amino acid segment of MPRIP protein, inhibiting its downstream glycolysis signaling pathway and suppressing NSCLC cells progression. In addition, macrophage coculture assay suggested that HVEM overexpression inhibited M2 macrophage polarization through GM-CSF/GM-CSFRα axis. In summary, our study has demonstrated that tumor cell intrinsic HVEM is a potential tumour metastasis suppressor, which may serve as a potential target for immunotherapy.

Immunogenic cell death signature predicts survival and reveals the role of VEGFA + Mast cells in lung adenocarcinoma

Lung cancer is prevalent worldwide and is a major cause of cancer-related mortality. Despite being the primary model for immunotherapy research, the response rates of lung cancer patients to immunotherapy are unsatisfactory. Furthermore, research on immunogenic cell death (ICD) in lung cancer is limited, which limits the development of strategies that combine ICD-related therapies with immunotherapy. In this study, we compiled and summarized 69 genes associated with ICD and developed an IRS. Across seven independent datasets, the IRS was identified as an independent prognostic factor. IRS was positively associated with multiple tumor proliferation pathways and negatively associated with immune-related pathways. Additionally, IRS negatively correlated with the infiltration of various immune cells, supporting its association with survival outcomes. Based on the correlation between IRS and immune activity, we validated the ability of IRS to predict immunotherapy efficacy across seven immunotherapy datasets and demonstrated that patients who respond to immunotherapy tend to have a lower IRS. Moreover, utilizing single-cell RNA sequencing, we revealed the role of mast cells in the TME with the highest IRS. Through interactions with various receptors on macrophages, endothelial cells, and tumor cells, mast cells promote tumor progression, providing a comprehensive explanation for poor prognosis and lack of response to immunotherapy in patients with high IRS. Our study offers new guidance for combination therapies in lung adenocarcinoma patients and elucidated the mechanism by which mast cells contribute to cancer development within the TME.

Neoadjuvant triplet immune checkpoint blockade in newly diagnosed glioblastoma

Glioblastoma (GBM) is an aggressive primary adult brain tumor that rapidly recurs after standard-of-care treatments, including surgery, chemotherapy and radiotherapy. While immune checkpoint inhibitor therapies have transformed outcomes in many tumor types, particularly when used neoadjuvantly or as a first-line treatment, including in melanoma brain metastases, they have shown limited efficacy in patients with resected or recurrent GBM. The lack of efficacy has been attributed to the scarcity of tumor-infiltrating lymphocytes (TILs), an immunosuppressive tumor microenvironment and low tumor mutation burden typical of GBM tumors, plus exclusion of large molecules from the brain parenchyma. We hypothesized that upfront neoadjuvant combination immunotherapy, administered with disease in situ, could induce a stronger immune response than treatment given after resection or after recurrence. Here, we present a case of newly diagnosed IDH-wild-type, MGMT promoter unmethylated GBM, treated with a single dose of neoadjuvant triplet immunotherapy (anti-programmed cell death protein 1 plus anti-cytotoxic T-lymphocyte protein 4 plus anti-lymphocyte-activation gene 3) followed by maximal safe resection 12 days later. The anti-programmed cell death protein 1 drug was bound to TILs in the resected GBM and there was marked TIL infiltration and activation compared with the baseline biopsy. After 17 months, there is no definitive sign of recurrence. If used first line, before safe maximal resection, checkpoint inhibitors are capable of immune activation in GBM and may induce a response. A clinical trial of first-line neoadjuvant combination checkpoint inhibitor therapy in newly diagnosed GBM is planned (GIANT; trial registration no. NCT06816927 ).

Effector T cells under hypoxia have an altered transcriptome similar to tumor-stressed T cells found in non-responsive melanoma patients

BACKGROUND

In the tumor microenvironment (TME), hypoxia stands as a significant factor that modulates immune responses, especially those driven by T cells. As T cell-based therapies often fail to work in solid tumors, this study aims to investigate the effects of hypoxia on T cell topo-distribution in the TME, gene expression association with T cell states, and clinical responses in melanoma.

METHODS

To generate detailed information on tumor oxygenation and T cell accessibility, we used mathematical modeling of human melanoma tissue microarrays that incorporate oxygen supply from vessels, intratumoral diffusion, and cellular uptake. We created tumor maps and derived plots showing the fraction of CD4 and CD8 T cells against the distance to the nearest vessel and oxygen pressure. To assess their function and transcriptional changes caused by hypoxia, effector T cells were generated and cultured under hypoxia (0.5% oxygen) or normoxia (21% oxygen). The T cell hypoxia-transcriptional signature was compared against datasets from msigDB, iATLAS (clinical trials of melanoma patients treated with immune checkpoint inhibitors (ICIs)), ORIEN AVATAR (real-world melanoma patients treated with ICIs), and a single-cell atlas of tumor-infiltrating lymphocytes.

RESULTS

We made three specific observations: (1) in melanoma T cells preferentially accumulated in oxygenated areas close to blood vessels (50-100 µm from the vasculature in the regions of high oxygen availability) but not in hypoxic areas far from blood vessels. (2) Our analysis confirmed that under hypoxia, T cell functions were significantly reduced compared with normoxic conditions and accompanied by a unique gene signature. Furthermore, this hypoxic gene signature was prevalent in resting and non-activated T cells. Notably and clinically relevant, the hypoxic T cell gene set was found to correlate with reduced overall survival and reduced progression-free survival in melanoma patients, which was more pronounced in non-responder patients undergoing ICI therapy. (3) Finally, compared with a single-cell atlas of tumor-infiltrating T cells, our hypoxia signature aligned with a population of cells at a state termed stress response state (TSTR).

CONCLUSIONS

Our study highlights the critical role of hypoxia in shaping T cell distribution and its correlation with clinical outcomes in melanoma. We revealed a preferential accumulation of T cells in oxygenated areas. Moreover, hypoxic T cells develop a distinct hypoxic gene signature prevalent in resting, non-activated T cells and TSTR that was also associated with poorer outcomes, particularly pronounced among non-responders to ICIs.

Mathematically mapping the network of cells in the tumor microenvironment

Cell-cell interaction (CCI) networks are key to understanding disease progression and treatment response. However, existing methods for inferring these networks often aggregate data across patients or focus on cell-type level interactions, providing a generalized overview but overlooking patient heterogeneity and local network structures. To address this, we introduce "random cell-cell interaction generator" (RaCInG), a model based on random graphs to derive personalized networks leveraging prior knowledge on ligand-receptor interactions and bulk RNA sequencing data. We applied RaCInG to 8,683 cancer patients to extract 643 network features related to the tumor microenvironment and unveiled associations with immune response and subtypes, enabling prediction and explanation of immunotherapy responses. RaCInG demonstrated robustness and showed consistencies with state-of-the-art methods. Our findings highlight RaCInG's potential to elucidate patient-specific network dynamics, offering insights into cancer biology and treatment responses. RaCInG is poised to advance our understanding of complex CCI s in cancer and other biomedical domains.

Spatial proteomics reveals sirtuin 1 to be a determinant of T-cell infiltration in human melanoma

BACKGROUND

The tumour microenvironment significantly influences the clinical response of patients to therapeutic immune checkpoint inhibition (ICI), but a comprehensive understanding of the underlying immune-regulatory proteome is still lacking.

OBJECTIVES

To decipher targetable biologic processes that determine tumour-infiltrating lymphocytes (TiLs) as a cellular equivalent of clinical response to ICI.

METHODS

We mapped the spatial distribution of proteins in TiL-enriched vs. TiL-low compartments in melanoma by combining microscopy, matrix-assisted laser desorption mass spectrometry imaging and liquid chromatography-mass spectrometry, as well as computational data mining. Pharmacological modulation of sirtuin 1 (SIRT1) activity in syngeneic mouse models was used to evaluate the efficacy of pharmacological SIRT1 activation in two syngeneic melanoma mouse models, one known to be α-programmed cell death protein 1 (PD-1) sensitive and the other α-PD-1 resistant.

RESULTS

Spatial proteomics and gene ontology-based enrichment analysis identified > 145 proteins enriched in CD8high tumour compartments, including negative regulators of mammalian target of rapamycin signalling such as SIRT1. Multiplexed immunohistochemistry confirmed that SIRT1 protein was expressed more in CD8high than in CD8low compartments. Further analysis of bulk and single-cell RNA sequencing data from melanoma tissue samples suggested the expression of SIRT1 by different lymphocyte subpopulations (CD8+ T cells, CD4+ T cells and B cells). Furthermore, we showed in vivo that pharmacological SIRT1 activation increased the immunological effect of α-PD-1 ICI against melanoma cells in mice, which was accompanied by an increase in T-cell infiltration and T-cell-related cytokines, including interferon (IFN)-γ, CCL4, CXCL9, CXCL10 and tumour necrosis factor-α. In silico analysis of large transcriptional data cohorts showed that SIRT1 was positively associated with the proinflammatory T-cell chemokines CXCL9, CXCL10 and IFN-γ, and prolonged overall survival of patients with melanoma.

CONCLUSIONS

Our study deciphers the proteomics landscape in human melanoma, providing important information on the tumour microenvironment and identifying SIRT1 as having important prognostic and therapeutic implications.

CDKN2A Low cancer cells outcompete macrophages for microenvironmental zinc to drive immunotherapy resistance

Approximately 50% of cancers exhibit decreased CDKN2A expression ( CDKN2A Low ), which is linked to immune checkpoint blockade (ICB) resistance. While CDKN2A is traditionally recognized as a tumor suppressor and cell cycle regulator, we have previously put forth a new paradigm demonstrating its role in intracellular metabolic reprogramming. Whether the metabolic derangement due to CDKN2A loss alters metabolites within the tumor microenvironment (TME) and how that affects the immune compartment and ICB response has never been investigated. Here we found that CDKN2A Low cancer cells reorganize zinc compartmentalization by upregulating the zinc importer SLC39A9 in the plasma membrane, leading to intracellular zinc accumulation in cancer cells and concurrent zinc depletion in the TME. This competition for zinc results in zinc-starved macrophages, leading to reduced phagocytic activity. Remarkably, restoring zinc levels in the TME through a dietary intervention re-educates macrophages to a pro-phagocytic phenotype, sensitizing CDKN2A Low tumors to ICB. Unexpectedly, T cells are not required for this response. Clinically, macrophages from CDKN2A Low cancer patients have decreased zinc signatures, corresponding to reduced phagocytosis signatures. Moreover, patients with low circulating zinc levels have reduced time-to-event outcomes compared to those with higher zinc levels. Our work reveals a previously unrecognized mechanism through which CDKN2A Low cancer cells outcompete macrophages for zinc, directly disrupting their function and ICB efficacy.

SPP1-mediated M2 macrophage polarization shapes the tumor microenvironment and enhances prognosis and immunotherapy guidance in nasopharyngeal carcinoma

Secreted phosphoprotein 1 (SPP1) shows carcinogenic potential in multiple cancers, yet its role in nasopharyngeal carcinoma (NPC) remains elusive. Leveraging transcriptomic data sourced from an NPC cohort at Fujian Cancer Hospital, alongside datasets from the Gene Expression Omnibus cohort and a single-cell RNA sequencing dataset, this investigation explored the role of SPP1 in tumor progression and the tumor microenvironment of NPC. A co-culture system involving tumor cells and macrophages was established to elucidate the relationship between SPP1 and tumor-associated macrophages in NPC. Subsequently, we established an SPP1-driven M2 macrophage signature using a machine-learning-based framework to predict patient prognosis. The results of our analysis indicated that SPP1 is associated with an elevated risk of disease progression and poor prognosis in NPC. Single-cell analysis demonstrated that SPP1 is a pivotal gene in the polarization of M2 macrophages within the tumor microenvironment. In vitro experiments demonstrated that NPC-derived SPP1 has the potential to activate the CD44/JAK2/STAT3 signaling pathway, promoting macrophage recruitment and polarization of the M2 subtype. Furthermore, we established a comprehensive SPP1-related M2 macrophage signature that can predict the prognosis and immune characteristics of patients with NPC. Our findings offer new insights into the role of SPP1 in the tumor microenvironment of NPC, and provide a novel SPP1-driven M2 macrophage signature with the potential to serve as a valuable tool for prognosis prediction and personalized therapy in NPC.

Overcoming immunotherapy resistance in hepatocellular carcinoma by targeting myeloid IL-8/CXCR2 signaling

Durable responses to immune checkpoint blockade (ICB) in hepatocellular carcinoma (HCC) are limited to a minority of patients, yet reliable biomarkers are still lacking. Inflammatory cytokines such as interleukin-8 (IL-8) are associated with HCC progression, and IL-8 is known as the chemoattractant for immunosuppressive myeloid cells. Therefore, we aim to elucidate the ICB resistance mechanisms mediated by the activation of the IL-8/CXCR2 pathway. Single-cell RNA sequencing (scRNA-seq) was performed in advanced HCC patients with baseline and on-treatment biopsy after pembrolizumab in a phase 2 clinical trial cohort. Our data revealed that IL-8 and its receptor, CXCR2, mainly derived from immunosuppressive myeloid-derived suppressor cells (MDSCs). In particular, the high circulating IL-8 level was strongly associated with poor ICB response. This myeloid IL-8/CXCR2 pathway was further elucidated in our ICB-resistant orthotopic mouse model using AZD5069, a clinically available CXCR2 antagonist. Suppression of the IL-8/CXCR2 pathway significantly abrogated MDSC trafficking and immunosuppressive activity, which sensitized the anti-PD-L1 blockade to reduce tumor growth and prolong survival. The association between myeloid IL-8 and ICB therapeutic outcomes also extended to multiple cancer types. Collectively, our study not only suggests a potential non-invasive biomarker for patient stratification and monitoring of ICB response but it also provides a proof of concept for combinational immunotherapy to benefit patients who are non-responsive to ICB monotherapy.

CBX2 suppresses interferon signaling to diminish tumor immunogenicity via a noncanonical corepressor complex

Chromobox 2 (CBX2), a crucial component of the polycomb repressive complex (PRC), has been implicated in the development of various human cancers. However, its role in the regulation of tumor immunogenicity and immune evasion remains inadequately understood. In this study, we found that ablation of CBX2 led to tumor growth inhibition, activation of the tumor immune microenvironment, and enhanced therapeutic efficacy of anti-PD1 or adoptive T cell therapies by using murine syngeneic tumor models. By analysis of the CBX2-regulated transcriptional program coupled with mass spectrometry screening of CBX2-interacting proteins, we found that CBX2 suppresses interferon signaling independent of its function in the canonical PRC. Mechanistically, CBX2 directly interacts with RACK1 and facilitates the recruitment of HDAC1, which attenuates the H3K27ac modification on the promoter regions of interferon-stimulated genes, thereby suppressing interferon signaling. Consequently, CBX2 reduces tumor immunogenicity and enables immune evasion. Moreover, a high expression level of CBX2 is associated with immune suppressive tumor microenvironment and reduced efficacy of immunotherapy across various human cancer types. Our study identifies a noncanonical CBX2-RACK1-HDAC1 corepressor complex in suppression of tumor immunogenicity, thereby presenting a potential target and biomarker for tumor immunotherapy.

Single-cell RNA Sequencing Analysis Reveals Cancer-associated Fibroblast Signature for Prediction of Clinical Outcomes and Immunotherapy in Gastric Cancer

Gastric cancer (GC) is a significant worldwide health concern and is a leading cause of cancer-related mortality. Immunotherapy has arisen as a promising strategy to stimulate the patient's immune system in combating cancer cells. Nevertheless, the effectiveness of immunotherapy in individuals with gastric cancer (GC) is not yet optimal. Thus, it is crucial to discover biomarkers capable appof predicting the advantages of immunotherapy for tailored treatment. The tumor microenvironment (TME) and its constituents, including cancer-associated fibroblasts (CAFs), exert a substantial influence on immune responses and treatment outcomes. In this investigation, we utilized single-cell RNA sequencing to profile CAFs in GC and established a scoring method, referred to as the CAF score (CAFS), for the prediction of patient prognosis and response to immunotherapy. Through our analysis, we successfully identified distinct subgroups within CAFs based on CAF score (CAFS), namely CAFS-high and CAFS-low subgroups. Notably, we noted that individuals within the CAFS-high subgroup experienced a lessF favorable prognosis and displayed diminished responsiveness to immunotherapy in contrast to the CAFS low subgroup. Furthermore, we analyzed the mutation and immune characteristics of these subgroups, identifying differentially mutated genes and immune cell compositions. We established that CAFS could forecast treatment advantages in patients with gastric cancer, both for chemotherapy and immunotherapy. Its efficacy was additionally confirmed in contrast to other biomarkers, including Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenotypic Score (IPS). These findings emphasize the clinical relevance and potential utility of CAFS in guiding personalized treatment strategies for gastric cancer.

Tertiary Lymphoid Structures are Linked to Enhanced Antitumor Immunity and Better Prognosis in Muscle-Invasive Bladder Cancer

The prognosis for muscle-invasive bladder cancer (MIBC) remains poor, and reliable prognostic markers have yet to be identified. Tertiary lymphoid structures (TLS) have been associated with favorable outcomes in certain cancers. However, the relationship between TLS and MIBC remains unclear. A multi-omics approach is utilized, leveraging single-cell RNA sequencing, spatial transcriptomics, bulk RNA sequencing, and immunohistochemistry, to investigate the roles of B cells and TLS in MIBC. These findings indicate that elevated levels of B cells and TLS correlate with improved prognoses in patients with MIBC, aligning with the robust antitumor immune responses observed in the TLS region. From a mechanistic perspective, CXCL13 serves as a critical cytokine for TLS formation in MIBC, primarily secreted by clonally expanded CXCL13+ T cells. This cytokine interacts with the CXCR5 receptor on NR4A2+ B cells, promoting TLS development. Plasma cells arising within the TLS microenvironment predominantly produce the IGHG antibody, potentially enhancing the phagocytic capabilities of C1QC+ macrophages. From an application standpoint, a TLS-specific gene signature is developed that effectively predicts outcomes in MIBC and other cancers. This study highlights the prognostic potential of TLS in MIBC and reveals immune mechanisms, offering insights for personalized treatment strategies.

A Distinguished Roadmap of Fibroblast Senescence in Predicting Immunotherapy Response and Prognosis Across Human Cancers

The resistance of tumors to immune checkpoint inhibitors (ICI) may be intricately linked to cellular senescence, although definitive clinical validation remains elusive. In this study, comprehensive pan-cancer scRNA-seq analyses identify fibroblasts as exhibiting the most pronounced levels of cellular senescence among tumor-associated cell populations. To elucidate this phenomenon, a fibroblast senescence-associated transcriptomic signature (FSS), which correlated strongly with protumorigenic signaling pathways and immune dysregulation that fosters tumor progression, is developed. Leveraging the FSS, the machine learning (ML) framework demonstrates exceptional accuracy in predicting ICI response and survival outcomes, achieving superior area under curve (AUC) values across validation, testing, and in-house cohorts. Strikingly, FSS consistently outperforms established signatures in predictive robustness across diverse cancer subtypes. From an integrative analysis of 17 CRISPR/Cas9 libraries, CDC6 emerges as a pivotal biomarker for pan-cancer ICI response and prognostic stratification. Mechanistically, experimental evidence reveals that CDC6 in tumor cells orchestrates fibroblast senescence via TGF-β1 secretion and oxidative stress, subsequently reprogramming the tumor microenvironment and modulating ICI response. These findings underscore the translational potential of targeting fibroblast senescence as a novel therapeutic strategy to mitigate immune resistance and enhance antitumor efficacy.

Combined PARP14 inhibition and PD-1 blockade promotes cytotoxic T cell quiescence and modulates macrophage polarization in relapsed melanoma

BACKGROUND

Programmed cell death 1 (PD-1) signaling blockade by immune checkpoint inhibitors (ICI) effectively restores immune surveillance to treat melanoma. However, chronic interferon-gamma (IFNγ)-induced immune homeostatic responses in melanoma cells contribute to immune evasion and acquired resistance to ICI. Poly ADP ribosyl polymerase 14 (PARP14), an IFNγ-responsive gene product, partially mediates IFNγ-driven resistance. PARP14 inhibition prolongs PD-1 blockade responses in preclinical models, but fails to achieve full tumor clearance, suggesting the involvement of additional resistance mechanisms.

METHODS

We identified a robust PARP14 catalytic inhibitor gene signature and evaluated its association with patient survival. Using preclinical models and single-cell RNA sequencing, we investigated immune and tumor cell adaptations to PARP14 inhibition combined with PD-1 blockade.

RESULTS

Combining PARP14 inhibition and PD-1 blockade suppressed tumor-associated macrophages while increasing proinflammatory memory macrophages. Moreover, this combination mitigated the terminal exhaustion of cytotoxic T cells by inducing a quiescent state, thereby preserving functionality. Despite the enhanced immune responses, tumor cells developed adaptive resistance by engaging alternative immune evasion pathways.

CONCLUSIONS

Although adaptive resistance mechanisms re-emerge, PARP14 inhibition combined with PD-1 blockade offers a promising strategy to enhance treatment outcomes and overcome ICI resistance in melanoma, as immune cells are primed for further therapeutic interventions that leverage the quiescent state.

Survival strategies of cancer cells: the role of macropinocytosis in nutrient acquisition, metabolic reprogramming, and therapeutic targeting

Macropinocytosis is a nonselective form of endocytosis that allows cancer cells to largely take up the extracellular fluid and its contents, including nutrients, growth factors, etc. We first elaborate meticulously on the process of macropinocytosis. Only by thoroughly understanding this entire process can we devise targeted strategies against it. We then focus on the central role of the MTOR (mechanistic target of rapamycin kinase) complex 1 (MTORC1) in regulating macropinocytosis, highlighting its significance as a key signaling hub where various pathways converge to control nutrient uptake and metabolic processes. The article covers a comprehensive analysis of the literature on the molecular mechanisms governing macropinocytosis, including the initiation, maturation, and recycling of macropinosomes, with an emphasis on how these processes are hijacked by cancer cells to sustain their growth. Key discussions include the potential therapeutic strategies targeting macropinocytosis, such as enhancing drug delivery via this pathway, inhibiting macropinocytosis to starve cancer cells, blocking the degradation and recycling of macropinosomes, and inducing methuosis - a form of cell death triggered by excessive macropinocytosis. Targeting macropinocytosis represents a novel and innovative approach that could significantly advance the treatment of cancers that rely on this pathway for survival. Through continuous research and innovation, we look forward to developing more effective and safer anti-cancer therapies that will bring new hope to patients.Abbreviation: AMPK: AMP-activated protein kinase; ASOs: antisense oligonucleotides; CAD: carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase; DC: dendritic cell; EGF: epidermal growth factor; EGFR: epidermal growth factor receptor; ERBB2: erb-b2 receptor tyrosine kinase 2; ESCRT: endosomal sorting complex required for transport; GAP: GTPase-activating protein; GEF: guanine nucleotide exchange factor; GRB2: growth factor receptor bound protein 2; LPP: lipopolyplex; MTOR: mechanistic target of rapamycin kinase; MTORC1: mechanistic target of rapamycin kinase complex 1; MTORC2: mechanistic target of rapamycin kinase complex 2; NSCLC: non-small cell lung cancer; PADC: pancreatic ductal adenocarcinoma; PDPK1: 3-phosphoinositide dependent protein kinase 1; PI3K: phosphoinositide 3-kinase; PIK3C3: phosphatidylinositol 3-kinase catalytic subunit type 3; PtdIns(3,4,5)P3: phosphatidylinositol-(3,4,5)-trisphosphate; PtdIns(4,5)P2: phosphatidylinositol-(4,5)-bisphosphate; PTT: photothermal therapies; RAC1: Rac family small GTPase 1; RPS6: ribosomal protein S6; RPS6KB1: ribosomal protein S6 kinase B1; RTKs: receptor tyrosine kinases; SREBF: sterol regulatory element binding transcription factor; TFEB: transcription factor EB; TNBC: triple-negative breast cancer; TSC2: TSC complex subunit 2; ULK1: unc-51 like autophagy activating kinase 1; UPS: ubiquitin-proteasome system.

Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients

Immune checkpoint blockade (ICB) therapies have emerged as a promising avenue for the treatment of various cancers. Despite their success, the efficacy of these treatments is variable across patients and cancer types. Numerous single-cell RNA-sequencing (scRNA-seq) studies have been conducted to unravel cell-specific responses to ICB treatment. However, these studies are limited in their sample sizes and require advanced coding skills for exploration. Here, we have compiled eight scRNA-seq datasets from nine cancer types, encompassing 223 patients, 90,270 cancer cells, and 265,671 other cell types. This compilation forms a unique resource tailored to investigate how cancer cells respond to ICB treatment across cancer types. We meticulously curated, quality-checked, pre-processed, and analyzed the data, ensuring easy access for researchers. Moreover, we designed a user-friendly interface for seamless exploration. By sharing the code and data for creating these interfaces, we aim to assist fellow researchers. These resources offer valuable support to those interested in leveraging and exploring single-cell datasets across diverse cancer types, facilitating a comprehensive understanding of ICB responses.

Signatures of H3K4me3 modification predict cancer immunotherapy response and identify a new immune checkpoint-SLAMF9

H3 lysine 4 trimethylation (H3K4me3) modification and related regulators extensively regulate various crucial transcriptional courses in health and disease. However, the regulatory relationship between H3K4me3 modification and anti-tumor immunity has not been fully elucidated. We identified 72 independent prognostic genes of lung adenocarcinoma (LUAD) whose transcriptional expression were closely correlated with known 27 H3K4me3 regulators. We constructed three H3K4me3 modification patterns utilizing the expression profiles of the 72 genes, and patients classified in each pattern exhibited unique tumor immune infiltration characteristics. Using the principal component analysis (PCA) of H3K4me3-related patterns, we constructed a H3K4me3 risk score (H3K4me3-RS) system. The deep learning analysis using 12,159 cancer samples from 26 cancer types and 725 cancer samples from 5 immunotherapy cohorts revealed that H3K4me3-RS was significantly correlated with cancer immune tolerance and sensitivity. Importantly, this risk-score system showed satisfactory predictive performance for the ICB therapy responses of patients suffering from several cancer types, and we identified that SLAMF9 was one of the immunosuppressive phenotype and immunotherapy resistance-determined genes of H3K4me3-RS. The mice melanoma model showed Slamf9 knockdown remarkably restrained cancer progression and enhanced the efficacy of anti-CTLA-4 and anti-PD-L1 therapies by elevating CD8 + T cell infiltration. This study provided a new H3K4me3-associated biomarker system to predict tumor immunotherapy response and suggested the preclinical rationale for investigating the roles of SLAMF9 in cancer immunity regulation and treatment.

Network-based transfer of pan-cancer immunotherapy responses to guide breast cancer prognosis

Breast cancer prognosis is complicated by tumor heterogeneity. Traditional methods focus on cancer-specific gene signatures, but cross-cancer strategies that provide deeper insights into tumor homogeneity are rarely used. Immunotherapy, particularly immune checkpoint inhibitors, results from variable responses across cancers, offering valuable prognostic insights. We introduced a network-based transfer (NBT) of pan-cancer immunotherapy responses to enhance breast cancer prognosis using node embedding and heat diffusion algorithms, identifying gene signatures netNE and netHD. Our results showed that netHD and netNE outperformed seven established breast cancer signatures in prognostic metrics, with netHD excelling. All nine gene signatures were grouped into three clusters, with netHD and netNE enriching the immune-related interferon-gamma pathway. Stratifying TCGA patients into two groups based on netHD revealed significant immunological differences and variations in 20 of 50 cancer hallmarks, emphasizing immune-related markers. This approach leverages pan-cancer insights to enhance breast cancer prognosis, facilitating insight transfer and improving tumor homogeneity understanding.Abstract graph of network-based insights translating pan-cancer immunotherapy responses to breast cancer prognosis. This abstract graph illustrates the conceptual framework for transferring immunotherapy response insights from pan-cancer studies to breast cancer prognosis. It highlights the integration of PPI networks to bridge genetic data and clinical phenotypes. The network-based method facilitates the identification of prognostic gene signatures in breast cancer by leveraging immunotherapy response information, providing a novel perspective on tumor homogeneity and its implications for clinical outcomes.

Distinct immune signatures for predicting the immunotherapy efficacy of esophageal squamous cell carcinoma or adenocarcinoma

Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are distinct histological subtypes of esophageal cancer. The tumor microenvironment of each subtype significantly influences the efficacy of immunotherapy. However, the characteristics of the tumor microenvironments of both subtypes, as well as their specific impacts on immunotherapy outcomes, still require further elucidation. Through the integration of gene expression profiles from ESCC and EAC obtained from The Cancer Genome Atlas database, alongside tumor tissues derived from Chinese patients, we identified TNFSF10, CXCL10, IL17RB, and CSF2 as pivotal immune molecules with significant prognostic implications. Elevated expression levels of TNFSF10 correlated with adverse outcomes in individuals diagnosed with ESCC. In contrast to patients from other geographical regions, CXCL10, IL17RB, and CSF2 exhibited distinct prognostic implications in Chinese patients with esophageal cancer. The Cox risk scores derived from the molecules TNFSF10 and CXCL10 for ESCC and IL17RB and CSF2 for EAC were used to assess their predictive capacity for immunotherapy efficacy. The results indicate that patients with lower Cox risk scores demonstrated an enhanced response to immunotherapeutic interventions. This study revealed significant disparities in the expression and functionality of immune-related molecules between ESCC and EAC and highlighted the potential of Cox risk scores derived from immune-related molecules to predict the efficacy of immunotherapy in patients. The findings underscore the clinical relevance of these biomarkers and emphasize the necessity for developing ethnic-specific biomarkers to guide personalized immunotherapy strategies between ESCC and EAC.

RECQL4 affects MHC class II-mediated signalling and favours an immune-evasive signature that limits response to immune checkpoint inhibitor therapy in patients with malignant melanoma

BACKGROUND

Cancer immunotherapy has transformed metastatic cancer treatment, yet challenges persist regarding therapeutic efficacy. RECQL4, a RecQ-like helicase, plays a central role in DNA replication and repair as part of the DNA damage response, a pathway implicated in enhancing efficacy of immune checkpoint inhibitor (ICI) therapies. However, its role in patient response to ICI remains unclear.

METHODS

We analysed whole exome and bulk RNA sequencing data from a pan-cancer cohort of 25 775 patients and cutaneous melanoma cohorts (untreated: n = 471, anti-progressive disease [PD]-1 treated: n = 212). RECQL4 copy number variations and expression levels were assessed for patient outcomes. We performed gene set enrichment analysis to identify RECQL4-dependent signalling pathways and explored the association between RECQL4 levels and immunoscores. We evaluated the interplay of ICI response and RECQL4 expression in melanoma cohorts of 95 responders and 85 non-responders prior to and after ICI-targeted therapy and tested the prognostic power of RECQL4. Finally, we generated genetically engineered RECQL4 variants and conducted comprehensive multi-omic profiling, employing techniques such as liquid chromatography with tandem mass spectrometry, to elucidate mechanistic insights.

RESULTS

We identified RECQL4 as a critical negative regulator of poor prognosis and response to ICI therapy, but also demonstrated its suitability as an independent biomarker in melanoma. High tumour purity and limited signatures of tumour immunogenicity associated with response to anti-PD-1 correlated with high RECQL4 activity. We found alterations in the secretion profile of immune regulatory factors and immune-related pathways robustly suppressed in tumours with high RECQL4 levels, underscoring its crucial role in fostering immune evasion. Mechanistically, we identified RECQL4-mediated regulation of major histocompatibility complex class II molecule expression and uncovered class II major histocompatibility complex transactivator as a mediator bridging this regulation.

CONCLUSIONS

Our findings unraveled the pivotal role of RECQL4 in immune modulation and its potential as both a predictive biomarker and therapeutic target for optimising immunotherapeutic strategies across various cancer types.

HIGHLIGHTS

High RECQL4 expression limits survival and can act as an independent prognostic factor in melanoma patients. RECQL4 has the potential to act as a negative feedback mediator of immune checkpoint-targeted therapy by limiting signatures associated with therapeutic efficacy. RECQL4 favours an immune-evasive phenotype by downregulating major histocompatibility complex class II molecules.

Comprehensive Analysis of a Dendritic Cell Marker Genes Signature to Predict Prognosis and Immunotherapy Response in Lung Adenocarcinoma

With the development of immune checkpoints inhibitors (ICIs), immunotherapy has recently taken center stage in cancer treatment. Dendritic cells exert complicated and important functions in antitumor immunity. This study aims to construct a novel dendritic cell marker gene signature (DCMGS) to predict the prognosis and immunotherapy response of lung adenocarcinoma (LUAD). DC marker genes in LUAD were identified by analysis of single-cell RNA sequencing data. 6 genes ( G0S2, KLF4, ALDH2, IER3, TXN, CD69 ) were screened as the most prognosis-related genes for constructing DCMGS on a training cohort from TCGA data set. Patients were divided into high-risk and low-risk groups by DCMGS risk score based on overall survival time. Then, the predictive ability of the risk model was validated in 6 independent cohorts. DCMGS was verified to be an independent prognostic factor in multivariate analysis. Furthermore, we performed pathway enrichment analysis to explore possible biological mechanisms of the powerful predictive ability of DCMGS, and immune cell infiltration landscape and inflammatory activities were exhibited to reflect the immune profile. Notably, we bridged DCMGS with expression of immune checkpoints and TCR/BCR repertoire diversity that can inflect immunotherapy response. Finally, the predictive ability of DCMGS in immunotherapy response was also validated by 2 cohorts that had received immunotherapy. As a result, the patients with lower DCMGS risk scores showed a better prognosis and immunotherapy response. In conclusion, DCMGS was suggested to be a promising prognostic indicator for LUAD and a desirable predictor for immunotherapy response.

Navigating the immune landscape with plasma cells: A pan-cancer signature for precision immunotherapy

Immunotherapy has revolutionized cancer treatment; however, predicting patient response remains a significant challenge. Our study identified a novel plasma cell signature, Plasma cell.Sig, through a pan-cancer single-cell RNA sequencing analysis, which predicts patient outcomes to immunotherapy with remarkable accuracy. The signature was developed using rigorous machine learning algorithms and validated across multiple cohorts, demonstrating superior predictive power with an area under the curve (AUC) exceeding 0.7. Notably, the low-risk group, as classified by Plasma cell.Sig, exhibited enriched immune cell infiltration and heightened tumor immunogenicity, indicating an enhanced responsiveness to immunotherapy. Conversely, the high-risk group showed reduced immune activity and potential mechanisms of immune evasion. These findings not only enhance understanding of the intrinsic and extrinsic immune landscapes within the tumor microenvironment but also pave the way for more precise, biomarker-guided immunotherapy approaches in oncology.

Cancer cells impair monocyte-mediated T cell stimulation to evade immunity

The tumour microenvironment is programmed by cancer cells and substantially influences anti-tumour immune responses1,2. Within the tumour microenvironment, CD8+ T cells undergo full effector differentiation and acquire cytotoxic anti-tumour functions in specialized niches3-7. Although interactions with type 1 conventional dendritic cells have been implicated in this process3-5,8-10, the underlying cellular players and molecular mechanisms remain incompletely understood. Here we show that inflammatory monocytes can adopt a pivotal role in intratumoral T cell stimulation. These cells express Cxcl9, Cxcl10 and Il15, but in contrast to type 1 conventional dendritic cells, which cross-present antigens, inflammatory monocytes obtain and present peptide-major histocompatibility complex class I complexes from tumour cells through 'cross-dressing'. Hyperactivation of MAPK signalling in cancer cells hampers this process by coordinately blunting the production of type I interferon (IFN-I) cytokines and inducing the secretion of prostaglandin E2 (PGE2), which impairs the inflammatory monocyte state and intratumoral T cell stimulation. Enhancing IFN-I cytokine production and blocking PGE2 secretion restores this process and re-sensitizes tumours to T cell-mediated immunity. Together, our work uncovers a central role of inflammatory monocytes in intratumoral T cell stimulation, elucidates how oncogenic signalling disrupts T cell responses through counter-regulation of PGE2 and IFN-I, and proposes rational combination therapies to enhance immunotherapies.

Thoracic Sarcopenia was a Poor Prognostic Predictor in Patients Receiving Immunotherapy for Advanced Non-small-cell Lung Cancer

RATIONALE AND OBJECTIVES

Sarcopenia, as measured at the level of the third lumbar (L3) has been shown to predict the survival of cancer patients. However, many patients with advanced non-small cell lung cancer (NSCLC) do not undergo routine abdominal imaging. The objective of this study was to investigate the association of thoracic sarcopenia with survival outcomes among patients who underwent immunotherapy for NSCLC.

MATERIALS AND METHODS

In this retrospective study, patients who initiated immunotherapy for advanced NSCLC from 2019 to 2022 were enrolled. and detailed patient data were collected. Cross sectional skeletal muscle area was calculated at the fifth thoracic vertebra (T5) on pretreatment chest computed tomography (CT) scan. Gender-specific lowest quartile values was used to define sarcopenia. The risk factors were analyzed using Cox analyses. The log-rank test and the random survival forest (RSF) were used to compare progression free survival (PFS). The model's performance was assessed using calibration curve and the receiver operating characteristic curve (ROC).

RESULTS

A total of 242 patients was included (discovery cohort n = 194, validation cohort n = 48). In the discovery cohort, patients with sarcopenia exhibited significantly poorer PFS (p < 0.001) than patients without sarcopenia. Univariate cox regression revealed that sarcopenia, lung cancer stage, body mass index, smoking status, and neutrophil-to-lymphocyte ratio were predictors of poor PFS. A RSF model was constructed based on the aforementioned parameters, to evaluate the model's efficacy, the ROC curve was utilized. with an area under the curve for predicting 6-month PFS of 0.68 and for 12-month PFS of 0.69. The prediction models for survival outcomes built by the discovery cohort showed similar performance in the validation cohort.

CONCLUSION

Sarcopenia at T5 is independent prognostic factors in patients who received immunotherapy for advanced NSCLC.

Optimizing T cell inflamed signature through a combination biomarker approach for predicting immunotherapy response in NSCLC

The introduction of anti-PD-1/PD-L1 therapies revolutionized treatment for advanced non-small cell lung cancer (NSCLC), yet response rates remain modest, underscoring the need for predictive biomarkers. While a T cell inflamed gene expression profile (GEP) has predicted anti-PD-1 response in various cancers, it failed in a large NSCLC cohort from the Stand Up To Cancer-Mark (SU2C-MARK) Foundation. Re-analysis revealed that while the T cell inflamed GEP alone was not predictive, its performance improved significantly when combined with gene signatures of myeloid cell markers. These additional signatures, however, showed negative contributions to prediction, hinting at immune alterations affecting therapy. Based on this, we proposed a combination biomarker approach that integrates the T cell inflamed GEP with immune-altered signatures, derived from the SU2C-MARK cohort using a machine-learning approach, as novel biomarkers. These signatures consisted of genes highly expressed in myeloid and stromal cells. We then assessed the predictive ability of these combined biomarkers in six independent cancer cohorts treated with anti-PD-1. The combined biomarkers demonstrated enhanced performance in NSCLC and gastric cancer cohorts, but not in melanoma cohorts. Our study introduces new biomarkers for predicting anti-PD-(L)1 response in NSCLC and offers mechanistic insights into treatment efficacy.

Protocol for using scCURE to construct an immunotherapy outcome prediction model

It is challenging to predict the immunotherapy outcome from the baseline status of patients with cancer. Here, we introduce a protocol for constructing an immunotherapy prediction model utilizing single-cell RNA sequencing (scRNA-seq)-based changed and unchanged cell recognition during immunotherapy (scCURE). Initially, we describe the steps for using scCURE to discriminate unchanged cells with similar cellular and molecular functions from whole scRNA-seq data. Subsequently, we demonstrate ways to construct immunotherapy outcome prediction models using either scRNA-seq or bulk RNA sequencing (RNA-seq) data, predicated on the unchanged cells identified by scCURE. For complete details on the use and execution of this protocol, please refer to Zou et al.1.

Tumor-Infiltrating Immune Cells and HLA Expression as Potential Biomarkers Predicting Response to PD-1 Inhibitor Therapy in Stage IV Melanoma Patients

PD-1 inhibitors are known to be effective in melanoma; however, a considerable proportion of patients fail to respond to therapy, necessitating the identification of predictive markers. We examined the predictive value of tumor cell HLA class I and II expression and immune cell infiltration in melanoma patients treated with PD-1 inhibitors. Pretreatment surgical samples from 40 stage IV melanoma patients were studied immunohistochemically for melanoma cell expression of HLA class I molecules (using four antibody clones with different specificities), HLA-II, and immune cell infiltration (using a panel of 10 markers). Among the responders, the ratio of patients showing melanoma cell HLA-II expression was higher compared to non-responders (p = 0.0158), and similar results were obtained in the case of two anti-HLA-I antibodies. A combined score of HLA-I/II expression also predicted treatment response (p = 0.0019). Intratumoral infiltration was stronger in the responders for most immune cell types. Progression-free survival showed an association with HLA-II expression, the combined HLA score, and the density of immune cells expressing CD134 and PD-1, while overall survival was significantly associated only with HLA class II expression. Our findings corroborate previous results indicating the importance of immune cell infiltration and tumor cell HLA-II expression in the efficacy of PD-1 inhibitor treatment in a "real world" patient cohort and suggest the potential predictive role of HLA class I expression.

Integrating necroptosis into pan-cancer immunotherapy: a new era of personalized treatment

Introduction

Necroptosis has emerged as a promising biomarker for predicting immunotherapy responses across various cancer types. Its role in modulating immune activation and therapeutic outcomes offers potential for precision oncology.

Methods

A comprehensive pan-cancer analysis was performed using bulk RNA sequencing data to develop a necroptosis-related gene signature, termed Necroptosis.Sig. Multi-omics approaches were employed to identify critical pathways and key regulators of necroptosis, including HMGB1. Functional validation experiments were conducted in A549 lung cancer cells to evaluate the effects of HMGB1 knockdown on tumor proliferation and malignancy.

Results

The Necroptosis.Sig gene signature effectively predicted responses to immune checkpoint inhibitors (ICIs). Multi-omics analyses highlighted HMGB1 as a key modulator of necroptosis, with potential to enhance immune activation and therapeutic efficacy. Functional experiments demonstrated that HMGB1 knockdown significantly suppressed tumor proliferation and malignancy, reinforcing the therapeutic potential of targeting necroptosis.

Discussion

These findings underscore the utility of necroptosis as a biomarker to guide personalized immunotherapy strategies. By advancing precision oncology, necroptosis provides a novel avenue for improving cancer treatment outcomes.

Induced B-Cell Receptor Diversity Predicts PD-1 Blockade Immunotherapy Response

Immune checkpoint inhibitors such as anti-PD-1 antibodies (aPD1) can be effective in treating advanced cancers. However, many patients do not respond and the mechanisms underlying these differences remain incompletely understood. In this study, we profile a cohort of patients with locally-advanced or metastatic basal cell carcinoma undergoing aPD-1 therapy using single-cell RNA sequencing, high-definition spatial transcriptomics in tumors and draining lymph nodes, and spatial immunoreceptor profiling, with long-term clinical follow-up. We find that successful responses to PD-1 inhibition are characterized by an induction of B-cell receptor (BCR) clonal diversity after treatment initiation. These induced BCR clones spatially co-localize with T-cell clones, facilitate their activation, and traffic alongside them between tumor and draining lymph nodes to enhance tumor clearance. Furthermore, we validated aPD1-induced BCR diversity as a predictor of clinical response in a larger cohort of glioblastoma, melanoma, and head and neck squamous cell carcinoma patients, suggesting that this is a generalizable predictor of treatment response across many types of cancers. We discover that pre-treatment tumors harbor a characteristic gene expression signature that portends a higher probability of inducing BCR clonal diversity after aPD-1 therapy, and we develop a machine learning model that predicts PD-1-induced BCR clonal diversity from baseline tumor RNA sequencing. These findings underscore a dynamic role of B cell diversity during immunotherapy, highlighting its importance as a prognostic marker and a potential target for intervention in non-responders.

Differential Infiltration of Key Immune T-Cell Populations Across Malignancies Varying by Immunogenic Potential and the Likelihood of Response to Immunotherapy

Background: Solid tumors vary by the immunogenic potential of the tumor microenvironment (TME) and the likelihood of response to immunotherapy. The emerging literature has identified key immune cell populations that significantly impact immune activation or suppression within the TME. This study investigated candidate T-cell populations and their differential infiltration within different tumor types as estimated from mRNA co-expression levels of the corresponding cellular markers. Methods: We analyzed the mRNA co-expression levels of cellular biomarkers that define stem-like tumor-infiltrating lymphocytes (TILs), tissue-resident memory T-cells (TRM), early dysfunctional T-cells, late dysfunctional T-cells, activated-potentially anti-tumor (APA) T-cells and Butyrophilin 3A (BTN3A) isoforms, utilizing clinical and transcriptomic data from 1892 patients diagnosed with melanoma, bladder, ovarian, or pancreatic carcinomas. Real-world data were collected under the Total Cancer Care Protocol and the Avatar® project (NCT03977402) across 18 cancer centers. Furthermore, we compared the survival outcomes following immune checkpoint inhibitors (ICIs) based on immune cell gene expression. Results: In melanoma and bladder cancer, the estimated infiltration of APA T-cells differed significantly (p = 4.67 × 10-12 and p = 5.80 × 10-12, respectively) compared to ovarian and pancreatic cancers. Ovarian cancer had lower TRM T-cell infiltration than melanoma, bladder, and pancreatic (p = 2.23 × 10-8, 3.86 × 10-28, and 7.85 × 10-9, respectively). Similar trends were noted with stem-like, early, and late dysfunctional T-cells. Melanoma and ovarian expressed BTN3A isoforms more than other malignancies. Higher densities of stem-like TILs; TRM, early and late dysfunctional T-cells; APA T-cells; and BTN3A isoforms were associated with increased survival in melanoma (p = 0.0075, 0.00059, 0.013, 0.005, 0.0016, and 0.041, respectively). The TRM gene signature was a moderate predictor of survival in the melanoma cohort (AUROC = 0.65), with similar findings in testing independent public datasets of ICI-treated patients with melanoma (AUROC 0.61-0.64). Conclusions: Key cellular elements related to immune activation are more heavily infiltrated within ICI-responsive versus non-responsive malignancies, supporting a central role in anti-tumor immunity. In melanoma patients treated with ICIs, higher densities of stem-like TILs, TRM T-cells, early dysfunctional T-cells, late dysfunctional T-cells, APA T-cells, and BTN3A isoforms were associated with improved survival.

Circulating immune landscape in melanoma patients undergoing anti-PD1 therapy reveals key immune features according to clinical response to treatment

Introduction

Immune checkpoint blockers (ICB) bring unprecedented clinical success, yet many patients endure immune mediated adverse effects and/or fail to respond. Predictive signatures of response to ICB and mechanisms of clinical efficacy or failure remain understudied. DC subsets, in network with conventional αβ T (Tconv), NK, γδ T and iNKT cells, harbor pivotal roles in tumor control, yet their involvement in response to ICB remained underexplored.

Methods

We performed an extensive longitudinal monitoring of circulating immune cells from melanoma patients treated with first-line anti-PD1, before (T0) and during treatment. We assessed the phenotypic and functional features of DC and effector cells' subsets by multi-parametric flow cytometry and ProcartaPlex® dosages.

Results

We revealed differences according to response to treatment and modulations of patterns during treatment, highlighting a strong link between the immune landscape and the outcome of anti-PD1 therapy. Responders exhibited higher frequencies of circulating cDC1s, CD8+ T cells, and γδ2+ T cells in central memory (CM) stage. Notably, we observed a distinct remodeling of ICP expression profile, activation status and natural cytotoxicity receptor patterns of immune subsets during treatment. Anti-PD1 modulated DCs' functionality and triggered deep changes in the functional orientation of Tconv and γδT cells.

Discussion

Overall, our work provides new insights into the immunological landscape sustaining favorable clinical responses or resistance to first-line anti-PD1 therapy in melanoma patients. Such exploration participates in uncovering the mechanism of action of anti-PD1, discovering innovative predictive signatures of response, and paves the way to design pertinent combination strategies to improve patient clinical benefits in the future.

Inflammatory response signature score model for predicting immunotherapy response and pan-cancer prognosis

Background

Inflammatory responses influence the outcome of immunotherapy and tumorigenesis by modulating host immunity. However, systematic inflammatory response assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers remain unexplored. Here, we investigated an inflammatory response score model to predict CIT responses and patient survival in a pan-cancer analysis.

Methods

We retrieved 12 CIT response gene expression datasets from the Gene Expression Omnibus database (GSE78220, GSE19423, GSE100797, GSE126044, GSE35640, GSE67501, GSE115821 and GSE168204), Tumor Immune Dysfunction and Exclusion database (PRJEB23709, PRJEB25780 and phs000452.v2.p1), European Genome-phenome Archive database (EGAD00001005738), and IMvigor210 cohort. The tumor samples from six cancers types: metastatic urothelial cancer, metastatic melanoma, gastric cancer, primary bladder cancer, renal cell carcinoma, and non-small cell lung cancer.We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm.

Findings

The model had high predictive accuracy in both the training and validation cohorts. During sub-group analysis, area under the curve (AUC) values of 0.82, 0.80, 0.71, 0.7, 0.67, and 0.64 were obtained for the non-small cell lung cancer, gastric cancer, metastatic urothelial cancer, primary bladder cancer, metastatic melanoma, and renal cell carcinoma cohorts, respectively. CIT response rates were higher in the high-scoring training cohort subjects (51%) than the low-scoring subjects (27%). The five-year survival rates in the high- and low score groups of the training cohorts were 62% and 21%, respectively, while those of the validation cohorts were 54% and 22%, respectively (P < 0·001 in all cases). Inflammatory response signature score derived from on-treatment tumor specimens are highly predictive of response to CIT in patients with metastatic melanoma. A significant correlation was observed between the inflammatory response scores and tumor purity. Regardless of the tumor purity, patients in the low score group had a significantly poorer prognosis than those in the high score group. Immune cell infiltration analysis indicated that in the high score cohort, tumor-infiltrating lymphocytes were significantly enriched, particularly effector and natural killer cells. Inflammatory response scores were positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may have benefited patients with high scores. Analysis of signature scores across different cancer types from The Cancer Genome Atlas revealed that the prognostic performance of inflammatory response scores for survival in patients who have not undergone immunotherapy can be affected by tumor purity. Interleukin 21 (IL21) had the highest weight in the inflammatory response model, suggesting its vital role in the prediction mode. Since the number of metastatic melanoma patients (n = 429) was relatively large among CIT cohorts, we further performed a co-culture experiment using a melanoma cell line and CD8 + T cell populations generated from peripheral blood monocytes. The results showed that IL21 therapy combined with anti-PD1 (programmed cell death 1) antibodies (trepril monoclonal antibodies) significantly enhanced the cytotoxic activity of CD8 + T cells against the melanoma cell line.

Conclusion

In this study, we developed an inflammatory response gene signature model that predicts patient survival and immunotherapy response in multiple malignancies. We further found that the predictive performance in the non-small cell lung cancer and gastric cancer group had the highest value among the six different malignancy subgroups. When compared with existing signatures, the inflammatory response gene signature scores for on-treatment samples were more robust predictors of the response to CIT in metastatic melanoma.

Integrated single-cell transcriptome and TCR profiles of hepatocellular carcinoma highlight the convergence on interferon signaling during immunotherapy

BACKGROUND

Despite the success of immune checkpoint inhibitor (ICI)-based combination therapies in hepatocellular carcinoma (HCC), its effectiveness remains confined to a subset of patients. The development of reliable, predictive markers is important for accurate patient stratification and further mechanistic understanding of therapy response.

METHODS

We comprehensively analyzed paired single-cell RNA transcriptome and T-cell repertoire profiles from 14 HCC ascites samples, collected from 7 patients before and after treatment with the combination of sintilimab (anti-PD-1) and bevacizumab (anti-VEGF).

RESULTS

We identify a widespread convergence on interferon (IFN) signaling across various immune cell lineages in treatment-responsive patients with HCC, indicating a common transcriptional state transition in the immune microenvironment linked to immunotherapy response in HCC. Strong IFN signaling marks CD8+ T cells with larger clonal expansion and enhanced cytotoxicity, macrophages toward M1-like polarization and strong T-cell recruitment ability, dendritic cells with increased antigen presentation capacity, as well as highly cytotoxic natural killer cells and activated B cells. By translating our finding to cohorts of patients with HCC, we demonstrate the specificity of IFN-signaling in the prognosis of patients with HCC and its ability to predict immunotherapy response.

CONCLUSIONS

This study provides a unique single-cell resource with clonal and longitudinal resolution during ICI therapy and reveals IFN signaling as a biomarker of immunotherapy response in HCC, suggesting a beneficial effect by combining IFN inducers with ICIs for patients with HCC.

Propafenone facilitates mitochondrial-associated ferroptosis and synergizes with immunotherapy in melanoma

BACKGROUND

Despite the successful application of immunotherapy, both innate and acquired resistance are typical in melanoma. Ferroptosis induction appears to be a potential strategy to enhance the effectiveness of immunotherapy. However, the relationship between the status of ferroptosis and the effectiveness of immunotherapy, as well as viable strategies to augment ferroptosis, remains unclear.

METHODS

A screening of 200 cardiovascular drugs obtained from the Food and Drug Administration-approved drug library was conducted to identify the potential ferroptosis sensitizer. In vitro and in vivo experiments explored the effects of propafenone on ferroptosis in melanoma. Animal models and transcriptomic analyses evaluated the therapeutic effects and survival benefits of propafenone combined with immune checkpoint blockades (ICBs). The relationship between propafenone targets and the efficacy of ICBs was validated using the Xiangya melanoma data set and publicly available clinical data sets.

RESULTS

Through large-scale drug screening of cardiovascular drugs, we identified propafenone, an anti-arrhythmia medication, as capable of synergizing with ferroptosis inducers in melanoma. Furthermore, we observed that propafenone, in combination with glutathione peroxidase 4 inhibitor RSL3, collaboratively induces mitochondrial-associated ferroptosis. Mechanistically, propafenone transcriptionally upregulates mitochondrial heme oxygenase 1 through the activation of the Jun N-terminal kinase (JNK)/JUN signaling pathway under RSL3 treatment, leading to overloaded ferrous iron and reactive oxygen species within the mitochondria. In xenograft models, the combination of propafenone and ferroptosis induction led to nearly complete tumor regression and prolonged survival. Consistently, propafenone enhances immunotherapy-induced tumorous ferroptosis and antitumor immunity in tumor-bearing mice. Significantly, patients exhibiting high levels of ferroptosis/JUN/HMOX1 exhibited improved efficacy of immunotherapy and prolonged progression-free survival.

CONCLUSIONS

Taken together, our findings suggest that propafenone holds promise as a candidate drug for enhancing the efficacy of immunotherapy and other ferroptosis-targeted therapies in the treatment of melanoma.

Lnc-H19-derived protein shapes the immunosuppressive microenvironment of glioblastoma

The immunosuppressive tumor microenvironment (TME) is a prominent feature of glioblastoma (GBM), the most lethal primary brain cancer resistant to current immunotherapies. The mechanisms underlying GBM-TME remain to be explored. We report that long non-coding RNA (LncRNA) H19 encodes an immune-related protein called H19-IRP. Functionally separated from H19 RNA, H19-IRP promotes GBM immunosuppression by binding to the CCL2 and Galectin-9 promoters and activating their transcription, thereby recruiting myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs), leading to T cell exhaustion and an immunosuppressive GBM-TME. H19-IRP, overexpressed in clinical GBM samples, acts as a tumor-associated antigen (TAA) presented by major histocompatibility complex class I (MHC-I). A circular RNA vaccine targeting H19-IRP (circH19-vac) triggers a potent cytotoxic T cell response against GBM and inhibits GBM growth. Our results highlight the unrevealed function of H19-IRP in creating immunosuppressive GBM-TME by recruiting MDSCs and TAMs, supporting the idea of targeting H19-IRP with cancer vaccine for GBM treatment.

Comprehensive genomic and spatial immune infiltration analysis of survival outliers in extensive-stage small cell lung cancer receiving first-line chemoimmunotherapy

BACKGROUND

A minority of patients with extensive-stage small cell lung cancer (ES-SCLC) exhibit prolonged survival following first-line chemoimmunotherapy, which warrants the use of reliable biomarkers. Here, we investigated the disparities in genomics and immune cell spatial distribution between long- and short-term survival of patients with ES-SCLC.

METHODS

We retrospectively recruited 11 long-term (>2 years) and 13 short-term (<9 months) ES-SCLC survivors receiving first-line chemoimmunotherapy. The samples were processed using targeted next-generation sequencing (tNGS), programmed death ligand-1 staining, multiplex immunohistochemical staining for immune cells (mIHC), tumor mutation burden (TMB), and chromosomal instability score measurements. The expression of putative genes in SCLC at the bulk and single-cell RNA-sequencing levels, as well as the role of putative genes in pan-cancer immunotherapy cohorts, were analyzed.

RESULTS

At the genomic level, a greater proportion of the smoking signature and higher TMB (>3.1) were associated with favorable survival. At the single-gene and pathway levels, tNGS revealed that MCL1 and STMN1 amplification and alterations in the apoptosis pathway were more common in short-term survivors, whereas alterations in the DLL3, KMT2B, HGF, EPHA3, ADGRB3, lysine deprivation, and HGF-cMET pathways were observed more frequently in long-term survivors. mIHC analysis of immune cells with different spatial distributions revealed that long-term survivors presented increased numbers of M1-like macrophages in all locations and decreased numbers of CD8+ T cells in the tumor stroma. Bulk transcriptomic analysis demonstrated that high levels of STMN1 and DLL3 represented an immune-suppressive tumor immune microenvironment (TIME), whereas HGF indicated an immune-responsive TIME. The expression levels of our putative genes were comparative in both TP53/RB1 mutant-type and TP53/RB1 wild-type. At the single-cell level, STMN1, MCL1, and DLL3 were highly expressed among all molecular subtypes (SCLC-A, SCLC-N, and SCLC-P), with STMN1 being enriched in cell division and G2M checkpoint pathways.

CONCLUSIONS

For ES-SCLC patients receiving first-line chemoimmunotherapy, alterations in DLL3, KMT2B, HGF, EPHA3, and ADGRB3 and a greater proportion of M1-like macrophages infiltration in all locations were predictors of favorable survival, while MCL1 and STMN1 amplification, as well as a greater proportion of CD8+ T cells infiltrating the tumor stroma, predicted worse survival.

Neoadjuvant vidutolimod and nivolumab in high-risk resectable melanoma: A prospective phase II trial

Intratumoral TLR9 agonists and anti-PD-1 produce clinical responses and broad immune activation. We conducted a single-arm study of neoadjuvant TLR9 agonist vidutolimod combined with anti-PD-1 nivolumab in high-risk resectable melanoma. In 31 evaluable patients, 55% major pathologic response (MPR) was observed, meeting primary endpoint. MPR was associated with necrosis, and melanophagocytosis with increased CD8+ tumor-infiltrating lymphocytes and plasmacytoid dendritic cells (pDCs) in the tumor microenvironment, and increased frequencies of Ki67+CD8+ T cells peripherally. MPRs had an enriched pre-treatment gene signature of myeloid cells, and response to therapy was associated with gene signatures of immune cells, pDCs, phagocytosis, and macrophage activation. MPRs gut microbiota were enriched for Gram-negative bacteria belonging to the Bacteroidaceae and Enterobacteriaceae families and the small subgroup of Gram-negative Firmicutes. Our findings support that combined vidutolimod and nivolumab stimulates a broad anti-tumor immune response and is associated with distinct baseline myeloid gene signature and gut microbiota. ClinicalTrials.gov identifier: NCT03618641.

A comprehensive investigation of associations between cell death pathways and molecular and clinical features in pan-cancer

BACKGROUND

Regulated cell death (RCD) pathways play significant roles in tumorigenesis. However, systematic investigation into correlations between RCD and various molecular and clinical features, particularly anti-tumor immunity and immunotherapy response in pan-cancer remains lacking.

METHODS

Using the single-sample gene set enrichment analysis, we quantified the activities of six RCD pathways (apoptosis, autophagy, ferroptosis, cuproptosis, necroptosis, and pyroptosis) in each cancer specimen. Then, we explored associations of these six RCD pathways with tumor immunity, genomic instability, tumor phenotypes and clinical features, and responses to immunotherapy and targeted therapies in pan-cancer by statistical analyses.

RESULTS

Our results showed that the RCD (except autophagy) activities were oncogenic signatures, as evidenced by their hyperactivation in late stage or metastatic cancer patients, positive correlations with tumor proliferation, stemness, genomic instability and intratumor heterogeneity, and correlation with worse survival outcomes in cancer. In contrast, autophagy was a tumor suppressive signature as its associations with molecular and clinical features in cancer shows an opposite pattern compared to the other RCD pathways. Furthermore, heightened RCD (except cuproptosis) activities were correlated with increased sensitivity to immune checkpoint inhibitors. Additionally, elevated activities of pyroptosis, autophagy, cuproptosis and necroptosis were associated with increased drug sensitivity in a broad spectrum of anti-tumor targeted therapies, while the elevated activity of ferroptosis was correlated with decreased sensitivity to numerous targeted therapies.

CONCLUSION

RCD (except autophagy) activities correlate with unfavorable cancer prognosis, while the autophagy activity correlate with favorable clinical outcomes. RCD (except cuproptosis) activities are positive biomarkers for anti-tumor immunity and immunotherapy response.

Lnc NEAT1 facilitates the progression of melanoma by targeting the miR-152-3p/CDK6 axis: An observational study

Long noncoding (Lnc) RNAs are novel regulators in melanoma. Lnc nuclear enriched autosomal transcript 1 (NEAT1) was reportedly upregulated in melanoma; however, the functional roles and mechanisms of Lnc NEAT1 need further investigation. Therefore, we used quantitative real-time PCR to determine the mRNA levels of Lnc NEAT1, miR-152-3p, and cyclin-dependent protein kinase 6 (CDK6). The protein level of CDK6 was determined by Western blot. Cell counting kit 8 and colony formation assays were used to assess cell proliferation. Cell migration was measured by wound healing and Transwell assays. Direct binding of the indicated molecules was verified by an RNA-binding protein immunoprecipitation assay and a dual luciferase reporter assay. The results revealed that Lnc NEAT1 and CDK6 were elevated, while miR-152-3p was downregulated in melanoma. Furthermore, Lnc NEAT1 was positively correlated with CDK6 expression and negatively correlated with miR-152-3p level. Furthermore, Lnc NEAT1 facilitated proliferation, migration, and invasion of melanoma cells. The underlying mechanism is that Lnc NEAT1 serves as a sponge for miR-152-3p to suppress the inhibitory effect of miR-152-3p on CDK6. Furthermore, the miR-152-3p/ CDK6 axis was implicated in the progression of melanoma accelerated by Lnc NEAT1. Taken together, Lnc NEAT1 may promote melanoma development by serving as an endogenous sponge of miR-152-3p, increasing CDK6 expression, and identifying a new target for the treatment of melanoma.

The classification of melanocytic gene signatures

Gene expression profiling technologies have revolutionized cell biology, enabling researchers to identify gene signatures linked to various biological attributes of melanomas, such as pigmentation status, differentiation state, proliferative versus invasive capacity, and disease progression. Although the discovery of gene signatures has significantly enhanced our understanding of melanocytic phenotypes, reconciling the numerous signatures reported across independent studies and different profiling platforms remains a challenge. Current methods for classifying melanocytic gene signatures depend on exact gene overlap and comparison with unstandardized baseline transcriptomes. In this study, we aimed to categorize published gene signatures into clusters based on their similar patterns of expression across clinical cutaneous melanoma specimens. We analyzed nearly 800 melanoma samples from six gene expression repositories and developed a classification framework for gene signatures that is resilient against biases in gene identification across profiling platforms and inconsistencies in baseline standards. Using 39 frequently cited published gene signatures, our analysis revealed seven principal classes of gene signatures that correlate with previously identified phenotypes: Differentiated, Mitotic/MYC, AXL, Amelanotic, Neuro, Hypometabolic, and Invasive. Each class is consistent with the phenotypes that the constituent gene signatures represent, and our classification method does not rely on overlapping genes between signatures. To facilitate broader application, we created WIMMS (what is my melanocytic signature, available at https://wimms.tanlab.org/), a user-friendly web application. WIMMS allows users to categorize any gene signature, determining its relationship to predominantly cited signatures and its representation within the seven principal classes.

Cell Identity and Spatial Distribution of PD-1/PD-L1 Blockade Responders

The programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) axis inhibits T cell activity, impairing anti-tumor immunity. Blocking this axis with therapeutic antibodies is one of the most promising anti-tumor immunotherapies. It has long been recognized that PD-1/PD-L1 blockade reinvigorates exhausted T (TEX) cells already present in the tumor microenvironment (TME). However, recent advancements in high-throughput gene sequencing and bioinformatic tools have provided researchers with a more granular and dynamic insight into PD-1/PD-L1 blockade-responding cells, extending beyond the TME and TEX populations. This review provides an update on the cell identity, spatial distribution, and treatment-induced spatiotemporal dynamics of PD-1/PD-L1 blockade responders. It also provides a synopsis of preliminary reports of potential PD-1/PD-L1 blockade responders other than T cells to depict a panoramic picture. Important questions to answer in further studies and the translational and clinical potential of the evolving understandings are also discussed.

Fatty acid metabolism constrains Th9 cell differentiation and antitumor immunity via the modulation of retinoic acid receptor signaling

T helper 9 (Th9) cells are interleukin 9 (IL-9)-producing cells that have diverse functions ranging from antitumor immune responses to allergic inflammation. Th9 cells differentiate from naïve CD4+ T cells in the presence of IL-4 and transforming growth factor-beta (TGF-β); however, our understanding of the molecular basis of their differentiation remains incomplete. Previously, we reported that the differentiation of another subset of TGF-β-driven T helper cells, Th17 cells, is highly dependent on de novo lipid biosynthesis. On the basis of these findings, we hypothesized that lipid metabolism may also be important for Th9 cell differentiation. We therefore investigated the differentiation and function of mouse and human Th9 cells in vitro under conditions of pharmacologically or genetically induced deficiency of the intracellular fatty acid content and in vivo in mice genetically deficient in acetyl-CoA carboxylase 1 (ACC1), an important enzyme for fatty acid biosynthesis. Both the inhibition of de novo fatty acid biosynthesis and the deprivation of environmental lipids augmented differentiation and IL-9 production in mouse and human Th9 cells. Mechanistic studies revealed that the increase in Th9 cell differentiation was mediated by the retinoic acid receptor and the TGF-β-SMAD signaling pathways. Upon adoptive transfer, ACC1-inhibited Th9 cells suppressed tumor growth in murine models of melanoma and adenocarcinoma. Together, our findings highlight a novel role of fatty acid metabolism in controlling the differentiation and in vivo functions of Th9 cells.

BET inhibition sensitizes innate checkpoint inhibitor resistant melanoma to anti-CTLA-4 treatment

Approximately 50% of melanoma patients fail to respond to immune checkpoint blockade (ICB), and acquired resistance hampers long-term survival in about half of initially responding patients. Whether targeting BET reader proteins, implicated in epigenetic dysregulation, can enhance ICB response rates and durability, remains to be determined. Here we show elevated BET proteins correlate with poor survival and ICB responses in melanoma patients. The BET inhibitor IBET151, combined with anti-CTLA-4, overcame innate ICB resistance however, sequential BET inhibition failed against acquired resistance in mouse models. Combination treatment response in the innate resistance model induced changes in tumor-infiltrating immune cells, reducing myeloid-derived suppressor cells (MDSCs). CD4+ and CD8+ T cells showed decreased expression of inhibitory receptors, with reduced TIM3, LAG3, and BTLA checkpoint expression. In human PBMCs in vitro, BET inhibition reduced expression of immune checkpoints in CD4+ and CD8+ T cells, restoring effector cytokines and downregulating the transcriptional driver TOX. BET proteins in melanoma may play an oncogenic role by inducing immune suppression and driving T cell dysfunction. The study demonstrates an effective combination for innately unresponsive melanoma patients to checkpoint inhibitor immunotherapy, yet highlights BET inhibitors' limitations in an acquired resistance context.

Stratified analysis identifies HIF-2α as a therapeutic target for highly immune-infiltrated melanomas

While immune-checkpoint blockade (ICB) has revolutionized treatment of metastatic melanoma over the last decade, the identification of broadly applicable robust biomarkers has been challenging, driven in large part by the heterogeneity of ICB regimens and patient and tumor characteristics. To disentangle these features, we performed a standardized meta-analysis of eight cohorts of patients treated with anti-PD-1 (n=290), anti-CTLA-4 (n=175), and combination anti-PD-1/anti-CTLA-4 (n=51) with RNA sequencing of pre-treatment tumor and clinical annotations. Stratifying by immune-high vs -low tumors, we found that surprisingly, high immune infiltrate was a biomarker for response to combination ICB, but not anti-PD-1 alone. Additionally, hypoxia-related signatures were associated with non-response to anti-PD-1, but only amongst immune infiltrate-high melanomas. In a cohort of scRNA-seq of patients with metastatic melanoma, hypoxia also correlated with immunosuppression and changes in tumor-stromal communication in the tumor microenvironment (TME). Clinically actionable targets of hypoxia signaling were also uniquely expressed across different cell types. We focused on one such target, HIF-2α, which was specifically upregulated in endothelial cells and fibroblasts but not in immune cells or tumor cells. HIF-2α inhibition, in combination with anti-PD-1, enhanced tumor growth control in pre-clinical models, but only in a more immune-infiltrated melanoma model. Our work demonstrates how careful stratification by clinical and molecular characteristics can be leveraged to derive meaningful biological insights and lead to the rational discovery of novel clinical targets for combination therapy.